05/10/2021: Our research now featured in a Lawrence Berkeley National Lab press release: “Deep Learning Tactics Speed Quantum Simulations”.
- 10/07/2021: Our paper “Reinforcement Learning for Many-Body Ground State Preparation inspired by Counter-Diabatic Driving” is now published in Physical Review X.
- 17/06/2021: Our paper with Markus Schmitt and Maxime Dupont was published in Scipost Physics: SciPost Phys. 10, 147 (2021).
- 01/06/2021: Friederike Metz from Okinawa Institute of Science and Technology joins the group as a visiting PhD student; she will work remotely on reinforcement learning to control quantum many-body sytems using matrix product states.
- 20/05/2021: Georgi Alexandrov wins gold medal at the national mathematics university olympiad: read more here (in Bulgarian).
- 26/04/2021: Two papers in collaboration with Christoph Fleckenstein published in Physical Review B: Phys. Rev. B 103, L140302, and Phys. Rev. B 103, 144307.
- 31/03/2021: Our paper “Noise-Robust End-to-End Quantum Control using Deep Autoregressive Policy Networks” is accepted in Proceedings of Machine Learning Research (to appear in August).
- 01/03/2021: new master students: Pavel Tashev and Stefan Petrov will work on reinforcement learning to disentangle quantum states
- 01/12/2020: new bachelor student: Hristo Tonchev will work on matrix-product states for simulation of quantum many-body systems.
- 15/11/2020: Marin Bukov receives “highly commended” International Quantum Technology Emerging Researcher 2020 Award by IOP Publishing.
- 15/09/2020: new bachelor student: Georgi Aleksandrov will work on reinforcement learning to control chaotic classical systems.